剑桥大学计算机科学与工程系24年暑校-概率机器学习方向

具体可见官网网址：

http://www.ellis.eng.cam.ac.uk/summer-school/

The Cambridge Ellis Unit Summer School on Probabilistic Machine Learning is from 15-19 July 2024 at the Department of Computer Science and Technology.

https://www.cl.cam.ac.uk/maps/

The Cambridge Ellis Unit Summer School on Probabilistic Machine Learning is a distinguished course offered to graduate students, researchers and professionals, featuring engaging experts in their respective field and/or world-recognized professionals speaking about advanced machine learning concepts.

Topics

Statistical Emulation

Uncertainty Quantification

Evaluation of Probablistic Models

Re-inforcement Learning

Application RL

Inference/PN

Application BO

Introduction to Diffusion Models

Normalising Flows

Deep Generative Models

Application of Diffusion Models

Variational Inference and Stein Discrepancy

Probablistic Models in Computer Vision and Graphics

Machine Learning and the Physical World

Venue

The Summer School will be in person and held at the Department of Computer Science and Technology.

You can see travel information here.

This is an inperson event but we will record talks when we can and put on our Youtube channel.

Fees

All attendees will need to cover their own accommodation and travel costs.

Travel awards are available for attendees from under-represented backgrounds. Those selected to attend will then be given a chance to apply for the travel grant. Please email ellis-admin@eng.cam.ac.uk for more information.

There are no fees to attend the Summer School.

Lunch and tea/coffee will be provided.

Apply

Those wishing to attend the Cambridge Ellis Machine Learning Summer School will need to complete this form:
https://forms.gle/RLWKLZJH9fQXBTPx6

You will also have to supply:

1.2 page CV

2.Letter of Reference: The writer should assess the qualities, characteristics, and capabilities of the person being recommended in terms of that individual’s abilities. The letter should address the applicant’s background and potential in Machine Learning, academic standing compared to other students, and how he or she would benefit from attending Cambridge Ellis Machine Learning Summer School. The referee should be a person that has some experience working together with the applicant. It can be for example a Ph.D. supervisor, a former employer or manager.

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